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subject:"Germany"
~isPartOf:"Working paper / Department of Econometrics and Business Statistics, Monash University"
~person:"Liang, Xuan"
~person:"Yang, Yanrong"
~subject:"Panel"
~subject:"United States"
~type:"book"
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Working paper / Department of Econometrics and Business Statistics, Monash University
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Interactive effects panel data models with general factors and regressors
Peng, Bin
;
Su, Liangjun
;
Westerlund, Joakim
;
Yang, Yanrong
-
2021
Persistent link: https://www.econbiz.de/10012697956
Saved in:
2
Semiparametric spatial autoregressive panel data model with fixed effects and time-varying coefficients
Liang, Xuan
;
Gao, Jiti
;
Gong, Xiaodong
-
2021
Persistent link: https://www.econbiz.de/10012614543
Saved in:
3
Time-varying panel data models with an additive factor structure
Liu, Fei
;
Gao, Jiti
;
Yang, Yanrong
-
2020
Persistent link: https://www.econbiz.de/10012610885
Saved in:
4
Nonparametric estimation in panel data models with heterogeneity and time-varyingness
Liu, Fei
;
Gao, Jiti
;
Yang, Yanrong
-
2019
Persistent link: https://www.econbiz.de/10012606705
Saved in:
5
Time-varying coefficient spatial autoregressive panel data model with fixed effects
Liang, Xuan
;
Gao, Jiti
;
Gong, Xiaodong
-
2019
Persistent link: https://www.econbiz.de/10012606718
Saved in:
6
Extent pursuit for cross-sectional dependence in large panels
Gao, Jiti
;
Pan, Guangming
;
Yang, Yanrong
;
Zhang, Bo
-
2019
Persistent link: https://www.econbiz.de/10012592809
Saved in:
7
Recursive estimation in large panel data models : theory and practice
Jiang, Bin
;
Yang, Yanrong
;
Gao, Jiti
;
Hsiao, Cheng
-
2017
Persistent link: https://www.econbiz.de/10011781991
Saved in:
8
Estimation of structural breaks in large panels with cross-sectional dependence
Gao, Jiti
;
Pan, Guangming
;
Yang, Yanrong
-
2016
Persistent link: https://www.econbiz.de/10011781747
Saved in:
9
Cross-sectional independence test for a class of parametric panel data models
Pan, Guangming
;
Gao, Jiti
;
Yang, Yanrong
;
Guo, Meihui
-
2015
Persistent link: https://www.econbiz.de/10011781344
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